A new method for high throughput screening has been developed based upon the inclusion of the target receptor in a flowing chromatographic system. In this approach, the receptor is immobilized on a solid support and the support packed into a small column. The test chemicals are passed through the column, over the immobilized target, and the time that it takes for the compounds to pass from the beginning of the column to its end is directly related to the strength of interaction between the target and the compound, i.e. the binding affinity of the ligand-receptor complex. Using this method, complex chemical and biological mixtures can be rapidly sorted between compounds that interact and do not interact with the disease-related target. At the same time, the compounds that bind to the target are themselves rapidly sorted between low, medium and high affinity binders. Thus, the method quickly provides a large amount of data with high information content. We have developed prototypes for the G-protein coupled receptor-based screening using the kappa, mu and delta subtypes of the opioid recpetor, beta-adrenergic receptors and various subtypes of the nicotinic receptor. The nicotinic receptor-based columns have been used to screen tobbaco smoke condensates and initial results indicate that previously unknown compounds have been identified. These compounds are being assessed for their pharmacological activity as competitive agonists and antagonists and non-competitive inhibitors. A study using non-competitive inhibitors and non-linear chromatography was conducted and demonstrated that the method can be used to identify and characterize the non-competitive inhibitors which bind in the central lumen of the receptor as well as at an extra-receptor site indentified as the quinacrine binding site. Chemometric analysis was used to develop quantitative structure-activity relationships (QSAR) and the resulting equations can be used to predict the pharmacological activity of a compound. Molecular modeling studies were used to describe and predict the interactions between the nicotinic receptors and non-competitive inhibitors. The computer-based studies have been used as the basis for a patent application entitled Computer-based model for identification and characterization for non-competitive inhibitors of nicotinic acetylcholine receptors and related ligand-gated ion channel receptors (ref number: E-158-2003/0-US-01).